I’m excited and proud to announce today that Datagen has closed $50M in Series B financing led by our new investor Andy Vitus from Scale Venture Partners, with participation from our existing investors TLV Partners, Viola Ventures and Spider Capital. Additional investors taking part in the round include financial funds Vintage IP, Viola Growth and others. Thank you to Scale Venture Partners and to all our investors whose belief in us enables us to substantially accelerate our growth with our total funding reaching $70m to date, and to take the data market for Computer Vision AI by storm.
When we first started Datagen back in 2018, Gil, my partner and Datagen CTO, and I had a vision of teaching AI to see the world through AI-powered 3D simulations. We knew that performance increases with data in the deep learning era, and that manual data acquisition is the #1 bottleneck holding the industry back from expediting orders of magnitude faster. Thanks to the traction we presented, alongside our broad market understanding and maturity, we secured $18.5M in funding exactly 11 months ago.
In these past 11 months, there were unbelievable leaps in Datagen’s traction, going hand-in-hand with the trend the industry has experienced. Our conversations with customers and domain experts have changed from ‘explain to me what synthetic data is’ to ‘how can I solve my tasks with synthetic data’. We no longer have to show the value of synthetic data to our customers, instead, they come to us to share their success stories.
And the progress this market has made ever since is simply enormous.
According to Anthony Goldbloom and Gartner, the future of data is simulation. Goldbloom, the founder and CEO of Kaggle, says that “Synthetic data is an incredibly promising way to increase dataset size and diversity and allow us to build stronger models across all computer vision use cases.” Gartner predicts that by 2024, “60% of the data generated will be synthetic data” and “that it will completely overshadow real data in AI models” by 2030.
Datagen is also leading the way for a new paradigm of AI development – Data-as-Code. Data-as-Code is to data what Infrastructure-as-Code is to infrastructure: It turns heavy operational processes into a seamless, easy-to-control programmable interface. Even more importantly, it’s an approach that data scientists and AI engineers are eagerly adopting.
With synthetic data, the training data is just an artifact of running code. The users gain full control over the content of their data and managing it becomes just as easy as managing code. Essentially, synthetic data means that AI models can be the product of pure code. Thus, Data-as-Code becomes an enabler for data-centric AI and a way to manage data programmatically in one unified streamline.
Synthetic data is not just another type of data, combined with additional streams of data it will create better-performing ML models. Synthetic data is the new generation of data for AI. As Datagen’s product and technology matures, we see an increasing number of use cases addressed and solved exclusively using simulation and synthetically generated data. This is a strong signal that a new way of developing AI models is already here, changing the way we bring Computer Vision applications to production.
Datagen will continue to unlock the potential of visual AI and be a trusted advisor for our Fortune 500 customers to develop their future products in the worlds of AR/VR/Metaverse, in-cabin vehicle safety, security, robotics, IoT security and more.
I always say to our team that Datagen is not about the code we develop or the product we build. Datagen is about people. And amongst the different types of DNAs companies build, at Datagen we’ve genuinely been proving that top-performing companies can be built in healthy ways, without compromising on culture, respect and personal growth mindset. People here want their colleagues to succeed as their top priority, which creates an extraordinary work environment and very special connections. When our people are happy, communicating and balanced – the organization overperforms as a whole.
Andy Vitus, Partner at Scale VP, who brings years of experience as an engineer, an entrepreneur and an investor, joins us on this journey and infuses substantial industry knowledge in creating products that developers love.
Andy sums it up like this – “As we enter a new, data-centric age of machine learning, a streamlined, operationalized data pipeline is poised to be the most lucrative piece of the machine learning puzzle, this is why we are placing our bets on Datagen, who is creating a complete CV stack that will propel advancements in AI — fundamentally transforming the way computer vision applications are developed and tested. The potential impact of what Datagen has to offer, across a broad range of applications, is staggering.”
We’re lucky to have investors on board who understand the future of AI and are thankful to have them on this journey with us.
Onward and upward!
Ofir Zuk (Chakon) is the co-founder and CEO of Datagen.